Integration: Mem0

pip install mem0-haystack

export MEM0_API_KEY="your-mem0-api-key"

from haystack.components.agents import Agent
from haystack.components.generators.chat import OpenAIChatGenerator
from haystack.components.generators.utils import print_streaming_chunk
from haystack.dataclasses import ChatMessage

from haystack_integrations.memory_stores.mem0 import Mem0MemoryStore
from haystack_integrations.tools.mem0 import (
    Mem0MemoryRetrieverTool,
    Mem0MemoryWriterTool,
)

store = Mem0MemoryStore()

retrieve_memories = Mem0MemoryRetrieverTool(memory_store=store, top_k=10)
store_memory = Mem0MemoryWriterTool(memory_store=store)

agent = Agent(
    chat_generator=OpenAIChatGenerator(model="gpt-5.4"),
    tools=[retrieve_memories, store_memory],
    system_prompt="""You are a helpful assistant with long-term memory.

At the beginning of each turn, call retrieve_memories without a query to inspect known memories.
Use store_memory only for new durable user-specific facts, preferences, or project context.
Before storing, compare the proposed memory with retrieved memories and avoid duplicates.
""",
    streaming_callback=print_streaming_chunk,
    state_schema={"user_id": {"type": str}},
)

agent.run(
    messages=[
        ChatMessage.from_user(
            "My name is Alice. Please remember that I prefer concise Python examples.",
        ),
    ],
    user_id="alice",
)

from haystack import Pipeline
from haystack.components.agents import Agent
from haystack.components.converters import OutputAdapter
from haystack.components.generators.chat import OpenAIChatGenerator
from haystack.components.generators.utils import print_streaming_chunk
from haystack.dataclasses import ChatMessage

from haystack_integrations.components.retrievers.mem0 import Mem0MemoryRetriever
from haystack_integrations.components.writers.mem0 import Mem0MemoryWriter
from haystack_integrations.memory_stores.mem0 import Mem0MemoryStore

store = Mem0MemoryStore()

pipeline = Pipeline()
pipeline.add_component("retriever", Mem0MemoryRetriever(memory_store=store, top_k=5))
pipeline.add_component(
    "memory_context",
    OutputAdapter(
        template="{{ memories + user_messages }}",
        output_type=list[ChatMessage],
        unsafe=True,
    ),
)
pipeline.add_component(
    "agent",
    Agent(
        chat_generator=OpenAIChatGenerator(model="gpt-5.4"),
        system_prompt="Use system messages at the start of the conversation as long-term memory.",
        streaming_callback=print_streaming_chunk,
    ),
)
pipeline.add_component("writer", Mem0MemoryWriter(memory_store=store, infer=True))

pipeline.connect("retriever.memories", "memory_context.memories")
pipeline.connect("memory_context.output", "agent.messages")
pipeline.connect("agent.messages", "writer.messages")

query = "Give me a short implementation tip."

pipeline.run(
    {
        "retriever": {
            "query": query,
            "user_id": "alice",
        },
        "memory_context": {
            "user_messages": [ChatMessage.from_user(query)],
        },
        "writer": {
            "user_id": "alice",
        },
    }
)